I am trying to fine tune easyocr and trying with small number of iteration 3K,batch size 128, and 24K images on RTX 3050 12GB. However it taking very long time to train. The following is the config file I am using:

manualSeed: 1111
workers: 4
batch_size: 128 #32
num_iter: 3000
valInterval: 200
FT: False
optim: False # default is Adadelta
lr: 1.
beta1: 0.9
rho: 0.95
eps: 0.00000001
grad_clip: 5
#Data processing
select_data: 'e' # this is dataset folder in train_data
batch_ratio: '1' 
total_data_usage_ratio: 1.0
batch_max_length: 35 
imgH: 64
imgW: 600
rgb: False
contrast_adjust: False
sensitive: True
PAD: True
contrast_adjust: 0.0
data_filtering_off: False
# Model Architecture
Transformation: 'None'
FeatureExtraction: 'ResNet'
SequenceModeling: 'BiLSTM'
Prediction: 'CTC'
num_fiducial: 20
input_channel: 1
output_channel: 512
hidden_size: 512
decode: 'greedy'
new_prediction: False
freeze_FeatureFxtraction: False
freeze_SequenceModeling: False